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Urbano- A New Tool to Promote Mobility-Aware Urban Design, Active Transportation Modeling and Access Analysis for Amenities and Public Transport

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Rapid urbanization, with new global construction estimated to be 250 times the floor area of NYC by 2050, is increasing traffic congestion, pollution and related health threats. This is a worrisome development but also a unique opportunity to improve urban mobility and quality of life. Understanding consequences of urban design choices on mobility, sustainability, and health is a necessity and requires development of a framework that enables such co-design processes. Existing transportation modelling tools are detached from the design process as they require technical expertise in traffic modelling, extensive preprocessing steps and heavy computational power, all of which make it difficult to be accessed by urban planners and designers. We propose a new, easy to use, CAD integrated, design-toolkit, called "Urbano", to model active transportation and to evaluate access to amenities and public transport. Urbano introduces a fully automated workflow to load in contextual GIS, OpenStreetMap and Google Places data to set up an urban mobility model. Kicking off by computing validated walkability metrics like a more flexible and modifiable version of the Walkscore, the tool will include other urban scale mobility metrics to aid the urban design process.
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... Its primary function is to simulate foot traffic patterns given the proximity of amenities such as schools, libraries, banks, restaurants, and cafes to people. The simulation setup and execution are performed in a three-step process [25]. The simulation environment is created by loading information from resources such as OSM, Google, Yelp, and the New York City Open Data Initiative into the software. ...
... The simulation environment is created by loading information from resources such as OSM, Google, Yelp, and the New York City Open Data Initiative into the software. The simulations executed by this software produce three metrics [25]. The first metric is a count of how many people used a given street segment during the simulation. ...
... Together these scores can be used to solve realworld problems quickly and cheaply by analyzing existing and proposed models in simulation environments. Several examples are included in [25]. In one example, two neighborhoods were compared to see which had better proximity to amenities overall. ...
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... Interchangeable [28,31,67,82,83,89] [ 17,18,63,72,77,80,91] [ 13,16,22,43,45,47,52,53,59,62,64,69,71,87] Superimposition [58] Explicit encoding [63] [ 47,53,85] vis systems heavily rely on interchangeable (27), followed by juxtaposition (7), and very few systems seem to use explicit encoding (2) and superimposition (1). Regarding designs drawn from 2D info-vis, we observe that most 3D urban vis systems do include 2D abstract visualizations (19). ...
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... Transport policy and design is aided by Urbano, which is a CAD integrated design toolkit designed to help analysing active transport modes and evaluates the accessibility to amenities and public transport. In addition, Urbano gives insight in the understanding of the implications of urban design choices in very early stages of an urban design process [12]. OSMnx is useful for acquiring, constructing, analysing, and visualising complex street networks. ...
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... Even in the American context, where large cities are more suburban than their international counterparts, inner-city areas have witnessed both residential and job growth in the past decade [13,14], pressuring city governments to respond with development plans that foster walkability. In order to forecast the effects that proposed built-environment changes could have on foot traffic, cities increasingly require quantitative models [15][16][17][18][19]. New real estate and infrastructure developments will not only fit into existing mobility patterns, but will themselves also influence travel behavior [20]. ...
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... Decay function for the Walkscore implementation. According to (Brewster et al. 2009) While the parameters in Table 5 are defined by the Walkscore metric, Urbano advances the Walkscore metric and can apply customized weighting to compute a personalized Walkscore (Dogan et al. 2018) or can adapt the amenity demand to local and demographic preferences (as shown in Figure 3). This flexibility enables, for example, time-based walkability analysis to evaluate walkability for morning, lunchtime, evening, and latenight activities, using schedules such as those shown in Table 3. ...
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DISCLAIMER The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated under the sponsorship of the Department of Transportation University Transportation Centers Program, in the interest of information exchange. The U.S. Government assumes no liability for the contents or use thereof.
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